How Transparency Policies Shape the Global Influence of Authoritarian Regimes on Social Media
Allison Koh
Centre for Artificial Intelligence in Government at
LSE Contentious Politics Workshop - November 15, 2024
Did the reversal of Twitter’s transparency policies increase the influence of authoritarian regimes?
Comparative case study: Official Government Accounts on Post-Musk Twitter
“We believe that people have the right to know when a media account is affiliated directly or indirectly with a state actor.”
– Twitter 2020
Sources: Internet Archive, Twitter
Sources: Internet Archive, Twitter
Source: Digital Forensic Research Lab
Erosion of transparency policies
⬇️
State actors took advantage of new opportunities for authoritarian image management1.
⬇️
They gained influence on the platform.
After each reversal of Twitter’s transprency policies…
| Feature | Hypotheses |
|---|---|
| Engagement | Reposts ⬆️; Likes ⬆️ |
| User Behavior | Post frequency ⬆️; Topic diversity ⬇️ |
State actors with high visibility will be less responsive to platform changes.
Do we observe differences in online behavior/engagement across countries?
1,177 accounts linked to Chinese, Iranian, and Russian state actors
Proxy for accounts that had government and state-affiliated media labels
twarc CLI
Tweet timeline endpoint; up to ~3,200 tweets per account
Collected ~2.5 million tweets from 1,038 timelines
⬆️ engagement with media; 🕸️ consolidation of messaging after label removal
Average per-user metrics
⬆️ engagement with Russian accounts; \(\Delta\) user behavior of Chinese + Russian accounts
Average per-user metrics
After Twitter’s erosion of transparency policies for state actors…
a.w.koh@bham.ac.uk
https://allisonkoh.github.io/
🦋 @allisonwkoh
Source: Rest of World, Lumen Database
Sources: DFRLab, Twitter, Internet Archive
After Twitter’s removal of profile labels on April 21st, 2023…
1,177 accounts linked to Chinese, Iranian, and Russian state actors
Proxy for accounts that had government and state-affiliated media labels
Per-day metrics 📈
⬆️ engagement with media; 🕸️ consolidation of messaging after label removal
Daily-aggregated totals/averages
⬆️ engagement with Russian accounts; \(\Delta\) user behavior of Chinese + Russian accounts
Daily-aggregated totals/averages
Placebo Tests—Engagement and Tweet Volume